Dr.  Sie Long  Kek
Universiti Tun Hussein Onn Malaysia (UTHM),  Malaysia

Title: Predictive Modelling with First-Order Linear Ordinary Differential Equations

Abstract:

Predictive modelling is a commonly used statistical approach to predict future outcomes by estimating parameters in a mathematical model with historical and current data, including a data-driven dynamic system. This talk employs a first-order linear ordinary differential equation (ODE) model to predict the solution of dynamic systems. We introduce a least squares optimization problem, where the objective function is a mean square of the differences between the system and the model used. Since the analytical solution of a first-order linear ODE model exists, we only update the model parameter iteratively using the gradient method and the data used. Once convergence is achieved, we obtain the optimal parameter that minimizes the differences. As a result, the model solution predicts the system solution satisfactorily. For illustration, some practical examples are studied, and their simulation results are presented. Hence, the accuracy of using the first-order linear ODE model for predicting dynamic systems is well expressed. Finally, the efficiency of the method proposed is verified.

Keywords: Predictive modelling, Ordinary differential equation, Least square optimization, gradient method, dynamic system

Biography:

Sie Long Kek, PhD, CQRM, is currently working as a senior lecturer in the Department of Mathematics and Statistics, Faculty of Applied Sciences and Technology, Universiti Tun Hussein Onn Malaysia (Pagoh Campus). He received his M.Sc. and Ph.D. in mathematics from Universiti Teknologi Malaysia, Johor, Malaysia in 2002 and 2011, respectively. He was a research associate at the Curtin University of Technology in 2009 during his Ph.D. study. His research interests include optimization and control, operational research and management science, modelling and simulation, parameter estimation, Kalman filtering, and computational mathematics. He has published more than 50 papers in refereed journals and six (6) book chapters. He is a reviewer for peer-reviewed research journals, including Automatica, Optimal Control, Applications and Methods, International Journal of Control, Heliyon, Journal of Industrial and Management Optimization, Measurement and Control, Hindawi Journal of Mathematics and MDPI Journal of Risk and Financial Management. He has hosted two (3) research projects supported by the Ministry of Education Malaysia. He has supervised five (5) master's and three (3) Ph.D. students. Since 2015, he is a certified quantitative risk management (CQRM) fellow. From 2021-2023, he was appointed as the head of the research focus group, Numerical Simulation and Applications (NSA).

Email: slkek@uthm.edu.my 

UTHM Staf Profile: https://community.uthm.edu.my/slkek 
SCOPUS ID: 35776335100
ORCID ID: 0000-0003-0425-4422
Publons ID: H-6498-2011
Google Scholar: https://scholar.google.com.my/citations?user=wWntPq4AAAAJ&hl=en